Predicting discomfort scores reported by LHD operators using whole-body vibration exposure values and musculoskeletal pain scores
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Laboratory studies have typically been used to establish a relationship between whole body vibration (WBV) magnitude, frequency, exposure duration and reported discomfort. However, the relationship between subjective reports of discomfort, and predicted comfort response according to International Standards Organization (ISO) 2631-1, predicted health risks according to ISO 2631-1 and reported musculoskeletal discomfort has not been examined. The purpose here was to compare discomfort values predicted by ISO 2631-1 with the subjective discomfort reported by nine Load-haul-dump (LHD) operators during typical operating conditions. METHODS: Vibration exposure at the operator/seat interface was measured and processed, for one-hour duration, according to criteria established in ISO 2631-1. Vibration total values were determined for 1-minute exposure periods and the LHD operators provided a discomfort score associated with the same vibration exposure period. A linear regression analysis and correlation was carried out to determine the strength of the relationship between the predicted subjective reports of discomfort, ISO 2631-1 discomfort, objectively measured acceleration levels and reported musculoskeletal discomfort. FINDINGS: Reported discomfort was poorly correlated to ISO discomfort scores (r=0.1799). Vibration exposure values and Musculo-Skeletal Disorder (MSD) variables were related to both ISO 2631-1 discomfort and to reported discomfort. The MSD scores produced stronger relationships with reported discomfort scores than did the vibration exposure values.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it